langchain: 0.2.13

Main entrypoint into package.

agents

agents.agent.AgentExecutor	Agent that is using tools.
agents.agent.AgentOutputParser	Base class for parsing agent output into agent action/finish.
agents.agent.BaseMultiActionAgent	Base Multi Action Agent class.
agents.agent.BaseSingleActionAgent	Base Single Action Agent class.
agents.agent.ExceptionTool	Tool that just returns the query.
agents.agent.MultiActionAgentOutputParser	Base class for parsing agent output into agent actions/finish.
agents.agent.RunnableAgent	Agent powered by Runnables.
agents.agent.RunnableMultiActionAgent	Agent powered by Runnables.
agents.agent_iterator.AgentExecutorIterator(...)	Iterator for AgentExecutor.
agents.agent_toolkits.vectorstore.toolkit.VectorStoreInfo	Information about a VectorStore.
agents.agent_toolkits.vectorstore.toolkit.VectorStoreRouterToolkit	Toolkit for routing between Vector Stores.
agents.agent_toolkits.vectorstore.toolkit.VectorStoreToolkit	Toolkit for interacting with a Vector Store.
agents.chat.output_parser.ChatOutputParser	Output parser for the chat agent.
agents.conversational.output_parser.ConvoOutputParser	Output parser for the conversational agent.
agents.conversational_chat.output_parser.ConvoOutputParser	Output parser for the conversational agent.
agents.mrkl.base.ChainConfig(action_name, ...)	Configuration for a chain to use in MRKL system.
agents.mrkl.output_parser.MRKLOutputParser	MRKL Output parser for the chat agent.
agents.openai_assistant.base.OpenAIAssistantAction	AgentAction with info needed to submit custom tool output to existing run.
agents.openai_assistant.base.OpenAIAssistantFinish	AgentFinish with run and thread metadata.
agents.openai_assistant.base.OpenAIAssistantRunnable	Run an OpenAI Assistant.
agents.openai_functions_agent.agent_token_buffer_memory.AgentTokenBufferMemory	Memory used to save agent output AND intermediate steps.
agents.output_parsers.json.JSONAgentOutputParser	Parses tool invocations and final answers in JSON format.
agents.output_parsers.openai_functions.OpenAIFunctionsAgentOutputParser	Parses a message into agent action/finish.
agents.output_parsers.openai_tools.OpenAIToolsAgentOutputParser	Parses a message into agent actions/finish.
agents.output_parsers.react_json_single_input.ReActJsonSingleInputOutputParser	Parses ReAct-style LLM calls that have a single tool input in json format.
agents.output_parsers.react_single_input.ReActSingleInputOutputParser	Parses ReAct-style LLM calls that have a single tool input.
agents.output_parsers.self_ask.SelfAskOutputParser	Parses self-ask style LLM calls.
agents.output_parsers.tools.ToolAgentAction	Fields:
agents.output_parsers.tools.ToolsAgentOutputParser	Parses a message into agent actions/finish.
agents.output_parsers.xml.XMLAgentOutputParser	Parses tool invocations and final answers in XML format.
agents.react.output_parser.ReActOutputParser	Output parser for the ReAct agent.
agents.schema.AgentScratchPadChatPromptTemplate	Chat prompt template for the agent scratchpad.
agents.structured_chat.output_parser.StructuredChatOutputParser	Output parser for the structured chat agent.
agents.structured_chat.output_parser.StructuredChatOutputParserWithRetries	Output parser with retries for the structured chat agent.
agents.tools.InvalidTool	Tool that is run when invalid tool name is encountered by agent.

callbacks

callbacks.streaming_aiter.AsyncIteratorCallbackHandler()	Callback handler that returns an async iterator.
callbacks.streaming_aiter_final_only.AsyncFinalIteratorCallbackHandler(*)	Callback handler that returns an async iterator.
callbacks.streaming_stdout_final_only.FinalStreamingStdOutCallbackHandler(*)	Callback handler for streaming in agents.
callbacks.tracers.logging.LoggingCallbackHandler(logger)	Tracer that logs via the input Logger.

chains

chains.base.Chain	Abstract base class for creating structured sequences of calls to components.
chains.combine_documents.base.BaseCombineDocumentsChain	Base interface for chains combining documents.
chains.combine_documents.map_reduce.MapReduceDocumentsChain	Combining documents by mapping a chain over them, then combining results.
chains.combine_documents.map_rerank.MapRerankDocumentsChain	Combining documents by mapping a chain over them, then reranking results.
chains.combine_documents.reduce.AsyncCombineDocsProtocol(...)	Interface for the combine_docs method.
chains.combine_documents.reduce.CombineDocsProtocol(...)	Interface for the combine_docs method.
chains.combine_documents.reduce.ReduceDocumentsChain	Combine documents by recursively reducing them.
chains.combine_documents.refine.RefineDocumentsChain	Combine documents by doing a first pass and then refining on more documents.
chains.constitutional_ai.base.ConstitutionalChain	Chain for applying constitutional principles.
chains.constitutional_ai.models.ConstitutionalPrinciple	Class for a constitutional principle.
chains.conversational_retrieval.base.BaseConversationalRetrievalChain	Chain for chatting with an index.
chains.conversational_retrieval.base.ChatVectorDBChain	Chain for chatting with a vector database.
chains.conversational_retrieval.base.InputType	Input type for ConversationalRetrievalChain.
chains.elasticsearch_database.base.ElasticsearchDatabaseChain	Chain for interacting with Elasticsearch Database.
chains.flare.base.FlareChain	Chain that combines a retriever, a question generator, and a response generator.
chains.flare.base.QuestionGeneratorChain	Chain that generates questions from uncertain spans.
chains.flare.prompts.FinishedOutputParser	Output parser that checks if the output is finished.
chains.hyde.base.HypotheticalDocumentEmbedder	Generate hypothetical document for query, and then embed that.
chains.llm_math.base.LLMMathChain	Chain that interprets a prompt and executes python code to do math.
chains.moderation.OpenAIModerationChain	Pass input through a moderation endpoint.
chains.natbot.base.NatBotChain	Implement an LLM driven browser.
chains.natbot.crawler.Crawler()	A crawler for web pages.
chains.natbot.crawler.ElementInViewPort	A typed dictionary containing information about elements in the viewport.
chains.openai_functions.citation_fuzzy_match.FactWithEvidence	Class representing a single statement.
chains.openai_functions.citation_fuzzy_match.QuestionAnswer	A question and its answer as a list of facts each one should have a source.
chains.openai_functions.openapi.SimpleRequestChain	Chain for making a simple request to an API endpoint.
chains.openai_functions.qa_with_structure.AnswerWithSources	An answer to the question, with sources.
chains.prompt_selector.BasePromptSelector	Base class for prompt selectors.
chains.prompt_selector.ConditionalPromptSelector	Prompt collection that goes through conditionals.
chains.qa_with_sources.loading.LoadingCallable(...)	Interface for loading the combine documents chain.
chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain	Question-answering with sources over an index.
chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain	Question-answering with sources over a vector database.
chains.query_constructor.base.StructuredQueryOutputParser	Output parser that parses a structured query.
chains.query_constructor.parser.ISO8601Date	A date in ISO 8601 format (YYYY-MM-DD).
chains.query_constructor.schema.AttributeInfo	Information about a data source attribute.
chains.question_answering.chain.LoadingCallable(...)	Interface for loading the combine documents chain.
chains.router.base.MultiRouteChain	Use a single chain to route an input to one of multiple candidate chains.
chains.router.base.Route(destination, ...)	Create new instance of Route(destination, next_inputs)
chains.router.base.RouterChain	Chain that outputs the name of a destination chain and the inputs to it.
chains.router.embedding_router.EmbeddingRouterChain	Chain that uses embeddings to route between options.
chains.router.llm_router.RouterOutputParser	Parser for output of router chain in the multi-prompt chain.
chains.router.multi_retrieval_qa.MultiRetrievalQAChain	A multi-route chain that uses an LLM router chain to choose amongst retrieval qa chains.
chains.sequential.SequentialChain	Chain where the outputs of one chain feed directly into next.
chains.sequential.SimpleSequentialChain	Simple chain where the outputs of one step feed directly into next.
chains.sql_database.query.SQLInput	Input for a SQL Chain.
chains.sql_database.query.SQLInputWithTables	Input for a SQL Chain.
chains.summarize.chain.LoadingCallable(...)	Interface for loading the combine documents chain.
chains.transform.TransformChain	Chain that transforms the chain output.

chat_models

embeddings

embeddings.cache.CacheBackedEmbeddings(...)

Interface for caching results from embedding models.

evaluation

evaluation.agents.trajectory_eval_chain.TrajectoryEval	A named tuple containing the score and reasoning for a trajectory.
evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain	A chain for evaluating ReAct style agents.
evaluation.agents.trajectory_eval_chain.TrajectoryOutputParser	Trajectory output parser.
evaluation.comparison.eval_chain.LabeledPairwiseStringEvalChain	A chain for comparing two outputs, such as the outputs
evaluation.comparison.eval_chain.PairwiseStringEvalChain	A chain for comparing two outputs, such as the outputs
evaluation.comparison.eval_chain.PairwiseStringResultOutputParser	A parser for the output of the PairwiseStringEvalChain.
evaluation.criteria.eval_chain.Criteria(value)	A Criteria to evaluate.
evaluation.criteria.eval_chain.CriteriaEvalChain	LLM Chain for evaluating runs against criteria.
evaluation.criteria.eval_chain.CriteriaResultOutputParser	A parser for the output of the CriteriaEvalChain.
evaluation.criteria.eval_chain.LabeledCriteriaEvalChain	Criteria evaluation chain that requires references.
evaluation.embedding_distance.base.EmbeddingDistance(value)	Embedding Distance Metric.
evaluation.embedding_distance.base.EmbeddingDistanceEvalChain	Use embedding distances to score semantic difference between a prediction and reference.
evaluation.embedding_distance.base.PairwiseEmbeddingDistanceEvalChain	Use embedding distances to score semantic difference between two predictions.
evaluation.exact_match.base.ExactMatchStringEvaluator(*)	Compute an exact match between the prediction and the reference.
evaluation.parsing.base.JsonEqualityEvaluator([...])	Evaluate whether the prediction is equal to the reference after
evaluation.parsing.base.JsonValidityEvaluator(...)	Evaluate whether the prediction is valid JSON.
evaluation.parsing.json_distance.JsonEditDistanceEvaluator([...])	An evaluator that calculates the edit distance between JSON strings.
evaluation.parsing.json_schema.JsonSchemaEvaluator(...)	An evaluator that validates a JSON prediction against a JSON schema reference.
evaluation.qa.eval_chain.ContextQAEvalChain	LLM Chain for evaluating QA w/o GT based on context
evaluation.qa.eval_chain.CotQAEvalChain	LLM Chain for evaluating QA using chain of thought reasoning.
evaluation.qa.eval_chain.QAEvalChain	LLM Chain for evaluating question answering.
evaluation.qa.generate_chain.QAGenerateChain	LLM Chain for generating examples for question answering.
evaluation.regex_match.base.RegexMatchStringEvaluator(*)	Compute a regex match between the prediction and the reference.
evaluation.schema.AgentTrajectoryEvaluator()	Interface for evaluating agent trajectories.
evaluation.schema.EvaluatorType(value[, ...])	The types of the evaluators.
evaluation.schema.LLMEvalChain	A base class for evaluators that use an LLM.
evaluation.schema.PairwiseStringEvaluator()	Compare the output of two models (or two outputs of the same model).
evaluation.schema.StringEvaluator()	Grade, tag, or otherwise evaluate predictions relative to their inputs and/or reference labels.
evaluation.scoring.eval_chain.LabeledScoreStringEvalChain	A chain for scoring the output of a model on a scale of 1-10.
evaluation.scoring.eval_chain.ScoreStringEvalChain	A chain for scoring on a scale of 1-10 the output of a model.
evaluation.scoring.eval_chain.ScoreStringResultOutputParser	A parser for the output of the ScoreStringEvalChain.
evaluation.string_distance.base.PairwiseStringDistanceEvalChain	Compute string edit distances between two predictions.
evaluation.string_distance.base.StringDistance(value)	Distance metric to use.
evaluation.string_distance.base.StringDistanceEvalChain	Compute string distances between the prediction and the reference.

globals

hub

indexes

indexes.vectorstore.VectorStoreIndexWrapper	Wrapper around a vectorstore for easy access.
indexes.vectorstore.VectorstoreIndexCreator	Logic for creating indexes.

memory

memory.buffer.ConversationBufferMemory	Buffer for storing conversation memory.
memory.buffer.ConversationStringBufferMemory	Buffer for storing conversation memory.
memory.buffer_window.ConversationBufferWindowMemory	Buffer for storing conversation memory inside a limited size window.
memory.chat_memory.BaseChatMemory	Abstract base class for chat memory.
memory.combined.CombinedMemory	Combining multiple memories' data together.
memory.entity.BaseEntityStore	Abstract base class for Entity store.
memory.entity.ConversationEntityMemory	Entity extractor & summarizer memory.
memory.entity.InMemoryEntityStore	In-memory Entity store.
memory.entity.RedisEntityStore	Redis-backed Entity store.
memory.entity.SQLiteEntityStore	SQLite-backed Entity store
memory.entity.UpstashRedisEntityStore	Upstash Redis backed Entity store.
memory.readonly.ReadOnlySharedMemory	Memory wrapper that is read-only and cannot be changed.
memory.simple.SimpleMemory	Simple memory for storing context or other information that shouldn't ever change between prompts.
memory.summary.ConversationSummaryMemory	Conversation summarizer to chat memory.
memory.summary_buffer.ConversationSummaryBufferMemory	Buffer with summarizer for storing conversation memory.
memory.token_buffer.ConversationTokenBufferMemory	Conversation chat memory with token limit.
memory.vectorstore.VectorStoreRetrieverMemory	VectorStoreRetriever-backed memory.
memory.vectorstore_token_buffer_memory.ConversationVectorStoreTokenBufferMemory	Conversation chat memory with token limit and vectordb backing.

model_laboratory

model_laboratory.ModelLaboratory(chains[, names])

Experiment with different models.

output_parsers

output_parsers.boolean.BooleanOutputParser	Parse the output of an LLM call to a boolean.
output_parsers.combining.CombiningOutputParser	Combine multiple output parsers into one.
output_parsers.datetime.DatetimeOutputParser	Parse the output of an LLM call to a datetime.
output_parsers.enum.EnumOutputParser	Parse an output that is one of a set of values.
output_parsers.fix.OutputFixingParser	Wrap a parser and try to fix parsing errors.
output_parsers.fix.OutputFixingParserRetryChainInput
output_parsers.pandas_dataframe.PandasDataFrameOutputParser	Parse an output using Pandas DataFrame format.
output_parsers.regex.RegexParser	Parse the output of an LLM call using a regex.
output_parsers.regex_dict.RegexDictParser	Parse the output of an LLM call into a Dictionary using a regex.
output_parsers.retry.RetryOutputParser	Wrap a parser and try to fix parsing errors.
output_parsers.retry.RetryOutputParserRetryChainInput
output_parsers.retry.RetryWithErrorOutputParser	Wrap a parser and try to fix parsing errors.
output_parsers.retry.RetryWithErrorOutputParserRetryChainInput
output_parsers.structured.ResponseSchema	Schema for a response from a structured output parser.
output_parsers.structured.StructuredOutputParser	Parse the output of an LLM call to a structured output.
output_parsers.yaml.YamlOutputParser	Parse YAML output using a pydantic model.

retrievers

retrievers.contextual_compression.ContextualCompressionRetriever	Retriever that wraps a base retriever and compresses the results.
retrievers.document_compressors.base.DocumentCompressorPipeline	Document compressor that uses a pipeline of Transformers.
retrievers.document_compressors.chain_extract.LLMChainExtractor	Document compressor that uses an LLM chain to extract the relevant parts of documents.
retrievers.document_compressors.chain_extract.NoOutputParser	Parse outputs that could return a null string of some sort.
retrievers.document_compressors.chain_filter.LLMChainFilter	Filter that drops documents that aren't relevant to the query.
retrievers.document_compressors.cross_encoder.BaseCrossEncoder()	Interface for cross encoder models.
retrievers.document_compressors.cross_encoder_rerank.CrossEncoderReranker	Document compressor that uses CrossEncoder for reranking.
retrievers.document_compressors.embeddings_filter.EmbeddingsFilter	Document compressor that uses embeddings to drop documents unrelated to the query.
retrievers.document_compressors.listwise_rerank.LLMListwiseRerank	Document compressor that uses Zero-Shot Listwise Document Reranking.
retrievers.ensemble.EnsembleRetriever	Retriever that ensembles the multiple retrievers.
retrievers.merger_retriever.MergerRetriever	Retriever that merges the results of multiple retrievers.
retrievers.multi_query.LineListOutputParser	Output parser for a list of lines.
retrievers.multi_query.MultiQueryRetriever	Given a query, use an LLM to write a set of queries.
retrievers.multi_vector.MultiVectorRetriever	Retrieve from a set of multiple embeddings for the same document.
retrievers.multi_vector.SearchType(value[, ...])	Enumerator of the types of search to perform.
retrievers.parent_document_retriever.ParentDocumentRetriever	Retrieve small chunks then retrieve their parent documents.
retrievers.re_phraser.RePhraseQueryRetriever	Given a query, use an LLM to re-phrase it.
retrievers.self_query.base.SelfQueryRetriever	Retriever that uses a vector store and an LLM to generate the vector store queries.
retrievers.time_weighted_retriever.TimeWeightedVectorStoreRetriever	Retriever that combines embedding similarity with recency in retrieving values.

runnables

runnables.hub.HubRunnable	An instance of a runnable stored in the LangChain Hub.
runnables.openai_functions.OpenAIFunction	A function description for ChatOpenAI
runnables.openai_functions.OpenAIFunctionsRouter	A runnable that routes to the selected function.

smith

smith.evaluation.config.EvalConfig	Configuration for a given run evaluator.
smith.evaluation.config.RunEvalConfig	Configuration for a run evaluation.
smith.evaluation.config.SingleKeyEvalConfig	Configuration for a run evaluator that only requires a single key.
smith.evaluation.progress.ProgressBarCallback(total)	A simple progress bar for the console.
smith.evaluation.runner_utils.ChatModelInput	Input for a chat model.
smith.evaluation.runner_utils.EvalError(...)	Your architecture raised an error.
smith.evaluation.runner_utils.InputFormatError	Raised when the input format is invalid.
smith.evaluation.runner_utils.TestResult	A dictionary of the results of a single test run.
smith.evaluation.string_run_evaluator.ChainStringRunMapper	Extract items to evaluate from the run object from a chain.
smith.evaluation.string_run_evaluator.LLMStringRunMapper	Extract items to evaluate from the run object.
smith.evaluation.string_run_evaluator.StringExampleMapper	Map an example, or row in the dataset, to the inputs of an evaluation.
smith.evaluation.string_run_evaluator.StringRunEvaluatorChain	Evaluate Run and optional examples.
smith.evaluation.string_run_evaluator.StringRunMapper	Extract items to evaluate from the run object.
smith.evaluation.string_run_evaluator.ToolStringRunMapper	Map an input to the tool.

storage

storage.encoder_backed.EncoderBackedStore(...)	Wraps a store with key and value encoders/decoders.
storage.file_system.LocalFileStore(root_path, *)	BaseStore interface that works on the local file system.